qc_todo

Placeholder implementations for functions that need to be implemented.

pyrnaither.stats.qc_todo.PdfPages(output_file)

Parameters:

output_file (str)

pyrnaither.stats.qc_todo.generate_replicate_matrix(data, min_reps, col, anno)

Generate a replicate matrix from the given data.

Return type:

Tuple[ndarray, List[int], List[int]]

Parameters:

• data (DataFrame)

• min_reps (int)

• col (str)

• anno (str)

Args:

data: DataFrame containing at least columns [col4val, col4anno]. min_reps: Minimum number of replicates required to keep an ID. col: name of the intensity column to fetch when index_or_int=”Intensities”. anno: name of the annotation column grouping replicates.

Returns:

replicate_matrix: 2D numpy array of shape (n_items, max_replicates), filled with

indices or values, using np.nan where missing.

index_pos_controls: list of row indices in replicate_matrix corresponding to positive controls. index_neg_controls: list of row indices in replicate_matrix corresponding to negative controls.

pyrnaither.stats.qc_todo.summarize_reps_no_filtering(data, col4val, col4anno)

Summarize replicates without filtering.

Return type:

DataFrame

Parameters:

• data (DataFrame)

• col4val (str)

• col4anno (str)

Args:

data: DataFrame containing at least columns [col4val, col4anno]. col4val: name of the intensity column to fetch when index_or_int=”Intensities”. col4anno: name of the annotation column grouping replicates.

Returns:

DataFrame with col4val